The present invention generally relates to photolithography, and more specifically relates to yield prediction tools for mask quality specifications.
Making a semiconductor device, such as an integrated circuit (IC), involves using photolithography to form patterns on a wafer, where the patterns correspond to complex circuitry. During the process, the patterns are initially formed on a reticle or mask, and then the patterns are exposed on the wafer by shining a light through, or illuminating, the mask.
A mask is typically a transparent silica (quartz) which contains a pattern, wherein opaque regions on the mask are formed of an ultraviolet light-absorbing layer, such as iron oxide. Typically, the pattern is created by a computer-controlled electron beam driven by the circuit layout data, using pattern generation software. A thin layer of electron beam sensitive material called electron beam resist is placed on the iron-oxide-covered quartz plate, and the resist is exposed by the electron beam. A resist is a thin organic polymer layer that undergoes chemical changes if it is exposed to energetic particles, such as electrons or protons. The resist is exposed selectively, corresponding to the patterns that are required. After exposure, the resist is developed in a chemical solution. The iron oxide layer is then selectively etched off in plasma to generate the appropriate patterns.
Depth of focus (DOF) indicates the range of distances around a focal plane where the image quality is sharp. It is important to optimize the illumination of a mask to achieve maximum common DOF, as this results in the best exposure of the wafer. Mask error factor limits the amount of a common process window which is useable.
Optical Proximity Correction (OPC) is common in the industry and involves the pre-compensation of predicted defects of a circuit design. Using empirical data, OPC software creates a mathematical description of the process distortions. Once this description is generated, automated software changes the shapes of the polygons in the pattern layout databases (libraries), moving segments of line edges and adding features that compensate the layout for the distortions to come. The critical layers of the photomask set can then be made using these modified, “pre-distorted” layout designs. When these masks are used to make chips, these predistortions will cancel the process distortions, resulting in better pattern fidelity, higher yield, and enhanced chip performance. FIG. 1 shows a pattern (i.e., polygon) 10 pre-OPC, and FIG. 2 shows the pattern post-OPC. As shown, OPC results in fragmentation 14 of the edges 12 of the polygon (i.e., to compensate the layout for distortions expected to come). After the edges 12 of the polygons are fragmented, post-OPC assembled masks are usually transformed (i.e., fractured) into a set of small primitives 16 before being passed to a mask vendor. This can be shown in the progression from FIG. 2 to FIG. 3.
Despite OPC, mask manufacturing process induces statistical errors, which can cause wafer yield loss (the loss sometimes being referred to as “mask error induced wafer yield loss”). Currently, there is a lack of adequate yield prediction tools for mask quality specifications. The approach currently used to attempt to solve the problem involves common process window analysis. However, common process window analysis is limited to a small set of features, and is not practical for full chip application. Furthermore, common process window analysis is not accurate with regard to predicting mask error induced wafer yield loss.